Target Screening Research Articles

Non-negligible Polyhalogenated Carbazoles in Arctic Soils and Sediments: Occurrence, Target and Suspect Screening, and Potential Sources.

The presence of polyhalogenated carbazoles (PHCZs), which are emerging as dioxin-like contaminants, in remote polar regions has not been reported. This study investigated 11 target PHCZs (Σ11PHCZs) and 25 unknown PHCZs (Σ25UNPs) in soil and sediment samples collected from Ny-Ålesund in the Arctic. The findings revealed that Σ11PHCZs concentrations reached 165.6 ng/g dry weight (dw), with 3,6-dichlorocarbazole and 3-chlorocarbazole being the predominant congeners. The Σ25UNPs concentrations ranged from 1.4 to 92.4 ng/g dw (median: 17.0 ng/g dw), primarily comprising a 1,3,6,8-tetrabromocarbazole isomer. The sediment contained ∼6 times more Σ25UNPs than Σ11PHCZs. Long-range atmospheric transport, oceanic transport, and human activity can potentially affect soils and sediments concurrently. For the first time, halogen substitution patterns in PHCZs, including ClI, ClI2, and ClI3, were detected in soil and sediment. Using the toxic equivalent (TEQ) approach, the potential toxic effects linked to the target PHCZ levels were assessed. The TEQPHCZs in Arctic soils and sediments indicated low risk, ranging from 8.0 × 10-3 to 17 pg TEQ/g dw (median: 2.8 pg TEQ/g dw) and 0.1 to 0.4 pg TEQ/g dw (median: 0.3 pg TEQ/g dw), respectively. This study marks the first report on the occurrence, composition, sources, and potential risks posed by PHCZs in the Arctic region.

RNA sequencing analysis uncovers the role of aldehyde oxidase TcAOX2 in regulating toxic substance susceptibility in the red flour beetle, Tribolium castaneum

Aldehyde oxidase (AOX) is a class of metabolic enzymes, which can make T. castaneum resistant to aldehyde insecticides and thus increase the difficulty of control. In this study, we first examined the killing effect of benzaldehyde, one of the main active components of mugwort essential oil, to T. castaneum and demonstrated the involvement of TcAOX2 in regulating the sensitivity of T. castaneum to benzaldehyde. Subsequently, we identified a total of 105 differentially expressed genes relative to controls by RNA sequencing (RNA-Seq) analysis of T. castaneum late larvae injected with dsTcAOX2, including 67 up-regulated and 38 down-regulated expressed genes. Analysis and functional annotation of differentially expressed genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The results showed that the expression of apolipoprotein D, carboxypeptidase A, serine protease P40, pancreatic triacylglycerol lipase, and other genes related to immunity and metabolism, their expression also decreased with the decrease of TcAOX2 expression. The down-regulation of the expression of these genes may make T. castaneum less immune and less able to cope with stressful environments. This suggests that changes in TcAOX2 gene expression may affect the expression of these metabolism- or immunity-related genes, which in turn affects T. castaneum sensitivity to external toxicants. In conclusion, our results provide a theoretical basis for exploring the detoxification mechanism of aldehyde oxidase in T. castaneum and for screening target genes in response to external stimuli.

Mechanisms Underlying the Therapeutic Effects of Yiqi Wenyang Huwei Decoction in Treating Asthma Based on GEO Datasets, Network Pharmacology, Experimental Validation, and Molecular Docking.

The Yiqi Wenyang Huwei Decoction (YWHD) is an herbal formula frequently utilized to treat asthma. Despite its wide usage, the specific mechanism of action remains unknown. Through an in-depth investigation utilizing network pharmacology, molecular docking techniques, and experimental validation, this study aims to uncover the molecular mechanism and material basis of YWHD in the treatment of asthma. The compounds and targets of YWHD were gathered from various databases such as TCMSP, PubMed, and CNKI. Additionally, asthma-related targets were obtained by combining the GEO dataset with GeneCards and OMIM databases. The STRING platform was employed to establish protein-protein interactions. GO and KEGG pathway enrichment analyses were conducted using DAVID. Molecular docking was utilized to assess the binding affinity between potential targets and active compounds. The asthma rat model was established through OVA induction, and a lung function meter was used to detect Mch-induced Max Rrs. HE staining was conducted to observe pathological changes, while ELISA was used to detect levels of inflammatory factors IL4, IL6, IL13, and IgE in BLAF. Furthermore, qPCR was used to detect levels of IL-1β, IL-6, JUN, and PTGS2 mRNA, while Western blot assay was employed to measure phosphorylation levels of NF-κB and IKKα. A comprehensive study revealed that YWHD has 188 active compounds and 250 corresponding targets. After conducting a topological analysis of the PPI network, the study identified 14 high-activity targets, including JUN, PTGS2, IL6, IL1B, CXCL8, MMP9, IL10, ALB, TGFB1, CCL2, IFNG, IL4, MAPK3, and STAT3. Further, GO and KEGG pathway enrichment analysis indicated that YWHD targets inflammation-related genes and regulates IL- 17 and NF-kappa B signaling pathways. Animal studies have shown that YWHD can effectively minimize airway Max Rrs, reduce the levels of inflammatory factors IL4, IL13, IL6, and IgE in BLAF, and improve airway inflammation in rats with asthma. Molecular experiments have also demonstrated that YWHD achieves this by down-regulating the expression levels of IL-1β, IL-6, JUN, and PTGS2 mRNA, inhibiting the phosphorylation modification levels of NF-κB and IKKα, and reducing the levels of inflammatory cytokines IL4, IL13, IL6, and IgE in BALF of rats. Interestingly, molecular docking has revealed that the active compounds in YWHD have a strong binding ability to the screening targets. This research endeavor systematically explicated the active constituents, prospective targets, and signaling pathways of YWHD for asthmatic intervention. The study provides an innovative notion and dependable resource for comprehending the molecular mechanism and pharmaceutical screening of YWHD in the context of asthma treatment.

BREAST CANCER SCREENING IN WOMEN AGED 45-65 IN SAMARKAND REGION, UZBEKISTAN: A CROSS-SECTIONAL ANALYSIS OF DATA FROM 2023

Objective: Breast cancer is a leading cause of cancer-related mortality among women globally, and early detection through screening significantly reduces morbidity and mortality. This study evaluates the outcomes of breast cancer screening programs in the Samarkand region of Uzbekistan in 2023, focusing on participation rates, detection rates, and stage distribution across 17 districts and cities. Methods: Data were collected on women aged 45–65, including annual screening targets, the number of screenings performed, diagnosed cases, and cancer stage distribution (early stages 1–2 vs. late stages 3–4). Statistical analysis was conducted to determine completion and detection rates, as well as regional disparities in screening outcomes. Results: The screening program achieved promising outcomes in participation and early-stage cancer detection, with substantial variability among districts. A higher proportion of cases were detected at stages 1–2, indicating effective early diagnosis in some areas. However, significant regional disparities in screening completion and detection highlight inequitable access to services. Novelty: This study provides a comprehensive regional analysis of breast cancer screening outcomes in Uzbekistan, emphasizing the importance of addressing disparities to improve equitable access to early diagnosis and treatment. These findings underscore the need for targeted public health interventions to enhance program effectiveness and reduce the burden of late-stage breast cancer

Mixtures of toxic organic micropollutants compromise the safety of water resources in urban agglomerations in low- and medium-income countries: The example of Lahore, Pakistan

Contamination of water resources with mixtures of organic micropollutants (OMP) including pesticides, pharmaceuticals, and industrial chemicals is a serious threat to aquatic organisms and human health. Long-term exposure to such pollutants may cause detrimental effects even at very low concentrations. Water resources in urban agglomerations in low- and medium-income countries may be under particular pressure due to high population densities, significant industrial activities, and limited water treatment and management resources. In these areas, many inhabitants directly rely on healthy urban water resources. Using the agglomeration of Lahore, Pakistan, as a case, we studied the occurrence, spatial distribution, and toxic risks of OMP mixtures in different urban water resources using target screening with liquid chromatography high-resolution mass spectrometry. In total, 266 of 576 target analytes were detected in at least one of the 200 samples taken from groundwater, canals, River Ravi and drains within the urban agglomeration. Notably, very high concentrations ranging from 10 to over 100 μg L−1 were found for highly toxic pesticides including several fungicides such as picoxystrobin, the transformation product phthalamic acid, and imazalil, the insecticide etofenprox but also industrial chemicals stemming for example from traffic such as 2-naphthalene sulfonic acid. Our study revealed high toxic risks particularly for invertebrates, fish and algae, with etofenprox as a dominant risk driver. This compound is extensively used in Lahore to control insect vectors of malaria and dengue fever in the urban agglomeration. Mixture risks were assessed using a toxic unit (TU) approach based on organism group specific effect concentrations, complemented with a risk quotient (RQ) approach using the lowest predicted no effect concentrations (PNECs). Acute and chronic risk thresholds were frequently exceeded, often by many orders of magnitude. These very high mixture risks strongly exceed those with previous studies in Europe, Africa and South America.

Navigating women's cancer prevention: Two cross-sectional studies to investigate psychosocial antecedents of cervical and breast cancer screening attendance.

Despite population-based cancer screening programmes effectively decreasing mortality, participation rates are unsatisfactory for both cervical and breast screening. This research tested an integrated theory of planned behaviour model applied to cervical cancer screening (CCS; Study 1) and breast cancer screening (BCS; Study 2) attendance. Women residing in Campania (Italy) and belonging to each screening target population joined two independent surveys (Study 1: n = 332, Mage = 41.03, SD = 11.45; Study 2: n = 298, Mage = 55.03; SD = 5.17). In both studies, screening behaviour was predicted by intention to undergo the screening, action and coping planning. Significant predictors of intention were subjective norms, perceived behavioural control and self-identity in Study 1, and subjective norms, anticipated regret and self-identity in Study 2. A mediation analysis confirmed the role of action and coping planning in the intention-behaviour relation. This model can guide forthcoming interventions and steer enhancements in healthcare access.

Network Pharmacology and Molecular Docking-Based Screening of Immunotherapeutic Targets for HuaChanSu Against Breast Cancer.

Breast cancer has emerged as the primary cause of mortality stemming from malignancies among women. HuaChanSu has demonstrated efficacy in suppressing the progression of various malignancies. However, the specific immune targets and pathways influenced by HuaChanSu within mammary tumors remain elusive. This study is designed to uncover potent monomers and pivotal targets associated with HuaChanSu's anti-breast cancer Immunotherapy. The genes pertinent to HuaChanSu and breast cancer were acquired individually from publicly available databases. Interaction analysis using Cytoscape was conducted on common genes to determine the most suitable targets and crucial constituents of HuaChanSu's Immunotherapy against breast cancer. Following this, molecular docking was employed to validate ligand and receptor binding interactions. Lastly, the identified core genes underwent assessment of immune infiltration. The intersection of HuaChanSu and BC targets yielded a total of 49 differentially expressed genes. Bufalin emerged as the most potent constituent in Immunotherapy. Immunoassay data demonstrated significant correlations (r > 0.03, p < 0.05) between S100B, MMP9, FOS, EGFR, KIT, MME, and immune infiltration within BC. Molecular docking further corroborated the effective binding of Bufalin with immune-related genes. Through network pharmacological validation, we propose the extraction of Bufalin, a monomeric constituent of Huachansu, to exert immunomodulatory effects aimed at inhibiting the progression of breast cancer. Most of the target genes (S100B, BIRC5, MMP9, FOS, EGFR, KIT, and MME) are common targets for immunotherapy.

In Vitro Biological Target Screening and Colloidal Aggregation of Minor Cannabinoids.

There is limited information on interactions between cannabinoids and many pharmacologically and toxicologically relevant targets in humans (e.g., receptors, ion channels, enzymes, and transporters). To address this data gap, seven cannabinoids were screened against a panel of 44 safety-related biological targets in competitive ligand binding or enzymatic activity assays. Diverse binding profiles were observed among the cannabinoids; however, colloidal aggregates were detected by dynamic light scattering and a detergent-sensitive enzyme inhibition assay. These aggregates may nonspecifically inhibit targets, yielding false positives. Although screening identified aggregates, additional testing is required to confirm cannabinoid aggregation in individual in vitro assays.

Machine learning-based prediction of elevated N terminal pro brain natriuretic peptide among US general population.

Natriuretic peptide-based pre-heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre-heart failure, has not been well established. This study evaluated the performance of machine learning prediction models for predicting elevated N terminal pro brain natriuretic peptide (NT-proBNP) levels in the US general population. Individuals aged 20-79years without cardiovascular disease from the nationally representative National Health and Nutrition Examination Survey 1999-2004 were included. Six prediction models (two conventional regression models and four machine learning models) were trained with the 1999-2002 cohort to predict elevated NT-proBNP levels (>125pg/mL) using demographic, lifestyle, and commonly measured biochemical data. The model performance was tested using the 2003-2004 cohort. Of the 10237 individuals, 1510 (14.8%) had NT-proBNP levels >125pg/mL. The highest area under the receiver operating characteristic curve (AUC) was observed in SuperLearner (AUC [95% CI]=0.862 [0.847-0.878], P<0.001 compared with the logistic regression model). The logistic regression model with splines showed a comparable performance (AUC [95% CI]=0.857 [0.841-0.874], P=0.08). Age, albumin level, haemoglobin level, sex, estimated glomerular filtration rate, and systolic blood pressure were the most important predictors. We found a similar prediction performance even after excluding socio-economic information (marital status, family income, and education status) from the prediction models. When we used different thresholds for elevated NT-proBNP, the AUC (95% CI) in the SuperLearner models 0.846 (0.830-0.861) for NT-proBNP>100pg/mL and 0.866 (0.849-0.884) for NT-proBNP>150pg/mL. Using nationally representative data from the United States, both logistic regression and machine learning models well predicted elevated NT-proBNP. The predictive performance remained consistent even when the models incorporated only commonly available variables in daily clinical practice. Prediction models using regularly measured information would serve as a potentially useful tools for clinicians to effectively identify targets of natriuretic-peptide screening.

The Atypical Neural Processing of Reward in Bipolar Disorder

Abstract: There are still many unanswered questions regarding bipolar disorder among researchers. Understanding the characteristics of a particular area and neuroeconomics can aid in a more thorough examination of reward dysfunction and the reward process. Because changes in reward are undoubtedly one of the most prevalent signs of psychopathology in humans, researchers try to understand the prevalence of these diseases as well as the importance of reward in the manifestation of these conditions. Research indicates that different biological entities with comparable phenotypic symptoms make up bipolar illness. Finding the primary and secondary rewards connected to the functioning resting-state of bipolar illness patients' brain circuits is the goal of another investigation. On the other hand, using a reward task that begins with the expectation and consumption of rewarding and nonrewarding outcomes and progresses through fixation point, target, and outcome screen, researchers hope to better understand the connections between healthy individuals and BD patients' reward processing and striatal responses. This review can provide some suggestions to the development of prevention and intervention programs for individuals at risk of BD.

Metabolic Flux Analysis of Xanthomonas oryzae Treated with Bismerthiazol Revealed Glutathione Oxidoreductase in Glutathione Metabolism Serves as an Effective Target.

Bacterial blight (BB) of rice caused by Xanthomonas oryzae pathovar oryzae (Xoo) is a serious global rice disease. Due to increasing bactericide resistance, developing new inhibitors is urgent. Drug repositioning offers a potential strategy to address this issue. In this study, we integrated transcriptional data into a genome-scale metabolic model (GSMM) to screen novel anti-Xoo targets. Two RNA-seq datasets (before and after bismerthiazol treatment) were used to constrain the GSMM and simulate metabolic processes. Metabolic fluxes were calculated using parsimonious flux balance analysis (pFBA) identifying reactions with significant changes for target screening. Glutathione oxidoreductase (GSR) was selected as a potential anti-Xoo target and validated through antibacterial experiments. Virtual screening based on the target identified DB12411 as a lead compound with the potential for new antibacterial agents. This approach demonstrates that integrating metabolic networks and transcriptional data can aid in both understanding antibacterial mechanisms and discovering novel drug targets.

Mechanism of Apigenin against breast cancer stem cells: network pharmacology and experimental validation.

Apigenin (API), a traditionally sourced flavonoid, is recognized for its anti-neoplastic properties. Despite well-documented effects on tumorigenesis, the detailed therapeutic impact on breast cancer stem cells (BCSCs) and the associated molecular mechanisms are yet to be clarified. The objective of this study is to elucidate the therapeutic effects of API on BCSCs and to uncover its molecular mechanisms through network pharmacology and experimental validation. Interactions of API with candidate targets were examined through target screening, enrichment analysis, construction of protein-protein interaction networks, and molecular docking. MCF-7-derived BCSCs were utilized as a model system to investigate and substantiate the anti-BCSC effects of API and the underlying mechanism. Molecular docking studies have shown that API and TP53 exhibit favorable binding affinity. Compared with the negative control group, API effectively suppressed the expression of BCSC-related proteins such as ALDH1A1, NANOG, EpCAM, and MYC, downregulated p-PI3K and p-AKT, and upregulated p53. This study demonstrates that API can play an anti-BCSC role by regulating the PI3K/AKT/p53 pathway in BCSCs of MCF-7 cells, highlighting its potential as a therapeutic agent for targeting BCSCs.

Predicting binding events in very flexible, allosteric, multi-domain proteins.

Knowledge of the structures formed by proteins and small molecules is key to understand the molecular principles of chemotherapy and for designing new and more effective drugs. During the early stage of a drug discovery program, it is customary to predict ligand-protein complexes in silico , particularly when screening large compound databases. While virtual screening based on molecular docking is widely used for this purpose, it generally fails in mimicking binding events associated with large conformational changes in the protein, particularly when the latter involve multiple domains. In this work, we describe a new methodology to generate bound-like conformations of very flexible and allosteric proteins bearing multiple binding sites by exploiting only information on the unbound structure and the putative binding sites. The protocol is validated on the paradigm enzyme adenylate kinase, for which we generated a significant fraction of bound-like structures. A fraction of these conformations, employed in ensemble-docking calculations, allowed to find native-like poses of substrates and inhibitors (binding to the active form of the enzyme), as well as catalytically incompetent analogs (binding the inactive form). Our protocol provides a general framework for the generation of bound-like conformations of challenging drug targets that are suitable to host different ligands, demonstrating high sensitivity to the fine chemical details that regulate protein's activity. We foresee applications in virtual screening, in the prediction of the impact of amino acid mutations on structure and dynamics, and in protein engineering.

Network Pharmacology and Molecular Dynamics Simulations Reveal the Mechanism of Total Alkaloid Components in Anisodus Tanguticus (Maxim.) Pascher in Treating Inflammation and Pain.

This study aimed to elucidate the mechanism that total alkaloids in Anisodus tanguticus (AT)(Maxim.) Pascher played anti-inflammatory and analgesic effects. In this paper, the anti-inflammatory effect in the total alkaloids of AT was confirmed via lipopolysaccharide (LPS)-induced inflammation model in RAW 264.7 cells and the main components of AT were immediately analyzed by UPLC/MS. Disease targets were obtained in GeneCards and DisGeNET. Targets of major compounds were searched in ETCM, TCMSP and other databases. The protein-protein interaction (PPI) network was constructed using STRING database, and Cytoscape was used for core targets screening. GO and KEGG enrichment analysis were performed using Daivid database. Sailvina was used for molecular docking. Molecular dynamics simulation analysis was performed using the Amber 20 program. The results showed that the main components in AT were anisodamine, atropine, fabiatrin, scopolamine, scopoletin and scopolin, possibly exerting anti-inflammatory and analgesic effects through pathways such as EGFR tyrosine kinase inhibitor resistance and IL-17 signaling pathway. Fabiatrin and scopolin could be potential drugs with good anti-inflammatory and analgesic effects.

In-silico Screening and Synthesis of Benzo[c]Pyridazines Targeting N-Methyl D-Aspartate Glutamate Receptor for the Treatment of Seizures.

This study focuses on synthesizing novel benzopyridazine compounds with an evaluation of their anti-epileptic activity by in-silico screening and MES test. The compounds were synthesized under controlled conditions by the reaction of the substituted anilines with sodium nitrite, followed by the reaction with cyanoacetamide, substituted urea, ethanol, and water. The final compounds (5a-d; 6a-d) were tested for antiepileptic activity by in-silico screening targeting N-Methyl D-Aspartate glutamate receptor (PDB ID:5IPV). The screened compounds are also evaluated by in vivo test (MES) by taking phenytoin as a standard drug. The results of the whole study were satisfactory with the yield of the compounds in the range of 88 % to 96 %. The results of in- silico, screening showed that compounds 6a and 6c have far more binding energy compared with standard phenytoin (6a -7.5 Kcal/mol. ; 6c -7.6 Kcal/mol. and Phenytoin -6.5 Kcal/mol.). The TD50 values of synthesized compounds (6a-6d) are observed to be significantly higher than those of standard phenytoin. The PI values of several synthetic compounds (6a and 6c) were found to be higher (55.8 % and 58.0 %) than the current antiepileptic medicine phenytoin (55.6 %), demonstrating the synthesized compound's safety potential.

Application of Nanoparticles in the Diagnosis and Treatment of Colorectal Cancer.

Colorectal cancer is a common malignant tumor with high morbidity and mortality rates, imposing a huge burden on both patients and the healthcare system. Traditional treatments such as surgery, chemotherapy and radiotherapy have limitations, so finding more effective diagnostic and therapeutic tools is critical to improving the survival and quality of life of colorectal cancer patients. While current tumor targeting research mainly focuses on exploring the function and mechanism of molecular targets and screening for excellent drug targets, it is crucial to test the efficacy and mechanism of tumor cell therapy that targets these molecular targets. Selecting the appropriate drug carrier is a key step in effectively targeting tumor cells. In recent years, nanoparticles have gained significant interest as gene carriers in the field of colorectal cancer diagnosis and treatment due to their low toxicity and high protective properties. Nanoparticles, synthesized from natural or polymeric materials, are NM-sized particles that offer advantages such as low toxicity, slow release, and protection of target genes during delivery. By modifying nanoparticles, they can be targeted towards specific cells for efficient and safe targeting of tumor cells. Numerous studies have demonstrated the safety, efficiency, and specificity of nanoparticles in targeting tumor cells, making them a promising gene carrier for experimental and clinical studies. This paper aims to review the current application of nanoparticles in colorectal cancer diagnosis and treatment to provide insights for targeted therapy for colorectal cancer while also highlighting future prospects for nanoparticle development.

Lycorine protects motor neurons against TDP-43 proteinopathy-induced degeneration in cross-species models with amyotrophic lateral sclerosis

Aggregation of TAR-DNA binding protein-43 (TDP-43) is a pathological feature present in nearly 97 % cases of amyotrophic lateral sclerosis (ALS), making it an attractive target for pathogenic studies and drug screening. Here, we have performed a high-throughput screening of 1500 compounds from a natural product library and identified that lycorine, a naturally occurring alkaloid, significantly decreases the level of TDP-43A315T in a cellular model. We further demonstrate that lycorine reduces the level of TDP-43A315T both through inhibiting its synthesis and by promoting its degradation by the ubiquitin-proteasome system (UPS). Importantly, treatment with lycorine significantly attenuates TDP-43 proteinopathy and improves functional recovery in TDP-43A315T-expressing Caenorhabditis elegans and mouse models. These findings suggest that lycorine is a promising lead compound that has therapeutic potential for ALS.

Metabolomic Profiling of Cerebrospinal Fluid Reveals Metabolite Biomarkers in Tick-Borne Encephalitis Patient.

Tick-borne encephalitis virus (TBEV) can cause life-threatening central nervous system infection. Changes in cerebrospinal fluid (CSF) metabolites may reflect critical aspects of host responses and end-organ damage in neuro infection and neuroinflammation. In this study, we applied an untargeted metabolomics screen of CSF samples to investigate the metabolites profile and explore biomarkers for TBEV infection. By analyzing CSF samples from 77 patients with TBEV infection and 23 without TBEV infection, tryptophan metabolism and Citrate cycle were found to be the top important metabolic pathways in differentiating the control and case groups; acetoacetate, 5'-deoxy-5'-(methylthio)-adenosine, 3-methyl-2-oxobutanoic acid, and so forth. were identified to be metabolic biomarkers (| FC|> 1, VIP > 1, FDR < 0.05) in CSF and clearly separated the TBEV infection from the noninfected samples. Moreover, four metabolites were identified to be associated with fatal outcome, including kynurenic acid, 5-hydroxyindole-3-acetic acid, DL-tryptophan, indole-3-acrylic acid, demonstrating the potential predictive biomarkers for severe TBEV infection. This study explored the metabolic profile of TBEV infection in CSF samples and identified candidate biomarkers for TBEV infection, which might be useful in target screening for differential diagnosis and therapeutic inter-vention.

Discovery and characterization of stereodefined PMO-gapmers targeting tau

Antisense oligonucleotides (ASOs) are an important class of therapeutics to treat genetic diseases, and expansion of this modality to neurodegenerative disorders has been an active area of research. To realize chronic administration of ASO therapeutics to treat neurodegenerative diseases, new chemical modifications that improve activity and safety profiles are still needed. Furthermore, it is highly desirable to develop a single stereopure ASO with a defined activity and safety profile to avoid any efficacy and safety concerns due to the batch-to-batch variation in the composition of diastereomers. Herein, a stereopure PMO-gapmer was developed as a new construct to improve safety and stability by installing charge-neutral PMOs at the wing region and by fully controlling phosphorus stereochemistries. The developed stereopure PMO-gapmer construct was applied to the discovery of ASO candidates for the reduction of microtubule-associated protein tau (MAPT, tau). Sequence screening targeting MAPT followed by screening of optimal phosphorus stereochemistry identified stereopure development candidates. While evaluating the stereopure PMO-gapmers, we observed a significant difference in safety profile among stereoisomers in which only one phosphorus stereochemistry differs. These results further highlight the benefits of developing stereopure ASOs as safe and well-characterized candidates for clinical studies.

ATTR cardiac amyloidosis after lumbar spinal stenosis- a prospective cohort study

Abstract Background Systemic wild type transthyretin (ATTRwt) amyloidosis is underdiagnosed and generally diagnosed in manifest cardiac disease. Lumbar spinal stenosis (LSS) might be an early sign of ATTRwt and a possible screening target for early diagnosis. Aim To characterize patients with transthyretin amyloid deposits in ligamentum flavum six years after surgery for lumbar spinal stenosis, and assess prevalence of undiagnosed cardiac amyloidosis. Materials and methods In this prospective cohort study, 21 patients who had surgery for LSS in 2016-2018 and grade 3-4 ATTR deposits in ligamentum flavum, without manifest cardiac amyloidosis (CA) were followed up in 2022-2023, including biomarkers and multimodality cardiac imaging. Results Median age at follow-up was 79 years and 62% were male; 16% (3/19) of patients had DPD-scintigraphy and were diagnosed with ATTRwt cardiac amyloidosis. 48% (10/21) had a history of other tenosynovial conditions that associate to ATTRwt amyloidosis. on echocardiography. Conclusion In this prospective cohort study, 16% of patients were diagnosed with ATTRwt cardiomyopathy after a median of six years following surgery for lumbar spinal stenosis. These findings strengthen the hypothesis that LSS is a possible manifestation of ATTRwt amyloidosis and that analysis for amyloid in connective tissue and subsequent cardiac follow-up is of value.